Multinomial Distribution Example. Three card players play a series of matches. The probability that player a will win any game is 20 the probability that player b will win is 30 and the probability player c will win is 50.
Using bayes rule is one of the major applications of multinomial distributions. A multinomial experiment will have a multinomial distribution. Bayes rule can be used to determine the probability of an event or outcome as mentioned above.
For example suppose that two chess players had played numerous games and it was determined that the probability that player a would win is 0 40 the probability that player b would win is 0 35 and the probability that the game would end in a draw is 0 25.
A multinomial experiment will have a multinomial distribution. For example suppose that two chess players had played numerous games and it was determined that the probability that player a would win is 0 40 the probability that player b would win is 0 35 and the probability that the game would end in a draw is 0 25. Using bayes rule is one of the major applications of multinomial distributions. A binomial experiment will have a binomial distribution.
